Adaptive Topology Control for Ad-hoc Sensor Networks

1. Adaptive Topology Control for Ad-hoc Sensor Networks 팀원 : 나종근, 박상하 정보통신연구실(INCLAB)

2. Contents • Adaptive Topology Control 소개 • GAF • Ya Xu et. al., “Geography-informed Energy Conservation for Ad Hoc Routing,” Mobicom’01 • STEM • Curt Schurgers et. al., “STEM : Topology Management for Energy Efficient Sensor Networks,” IEEE 2002

3. Adaptive Topology • Can we do more than shut down radio in between transmissions/receptions? • Can we put nodes to sleep for longer periods of time? • Goal: • Exploit high density (over) deployment to extend system lifetime • Provide topology that adapts to the application needs • Self-configuring system that adapts to environment without manual configuration

4. Adaptive Topology: Problem Description • Simple Formulation (Geometric Disk Covering) • Given a distribution of N nodes in a plane. • Place a minimum number of disks of radius r (centered on the nodes) to cover them. • Disk represents the radio connectivity (simple circle model). • The problem is NP-hard.

5. Connectivity Measurements*

6. Tradeoff • How many nodes to activate? • few active nodes: • distance between neighboring nodes high -> increase packet loss and higher transmit power and reduced spatial reuse; • need to maintain sensing coverage • too many active nodes: • at best, expending unnecessary energy; • at worst, nodes may interfere with one another by congesting the channel.

7. Adaptive Topology Schemes • Mechanisms being explored: • Empirical adaptation: Each node assesses its connectivity and adapts participation in multi-hop topology based on the measured operating region, ASCENT (Cerpa et al. 2002) • Cluster-based, load sharing within clusters, CEC (Xu et al. 2002) • Routing/Geographic topology based, eliminate redundant links, SPAN (Chen et al. 2001), GAF (Xu et al. 2001) • Data/traffic driven: Trigger nodes on demand using paging channel, STEM (Tsiatsis et al. 2002)

9. Some definition • Routing fidelity • Uninterrupted connectivity between communicating nodes • Fidelity • MSE • PSNR

12. Behavior of GAF (1/3) • GAF (Geographical Adaptive fidelity) • Virtual grid with GPS or other location information • All node in virtual grid are equivalent • Who will sleep and how long • Virtual grid • Divide the whole area into small “virtual grid” • For two adjacent grids A and B, all nodes in A can communicate with all nodes in B and vice versa • All nodes in each grid are equivalent for routing • Nodes exchange grid id to adjust their duty cycle • Grid id is determined by its location and grid size

13. Behavior of GAF (2/3) 6 What if node 1 dies? r: size of virtual grid R : radio transmission range

14. Behavior of GAF (3/3) • Three states • Sleeping, discovery, active Periodically re-broadcasts its discovery message Discovery message Initial state Node id Grid id Estimated node active time (enat) Node state

15. Tuning GAF • Estimated node active time (enat) • Node active duration (Ta) • Node ranking : longer enat  high-ranked node • Discovery message interval (Td) • A uniform random value between 0 and n • Node ranking : larger n  low-ranked node • Node sleep duration (Ts) • E.g. Uniform(enat/2, enat) • Node mobility should be considered

16. Mobility adaptation • engt: expected node grid time (speed) • engt = r/s • Sleep duration = min (enat, engt) • How about? • N highest ranking (e.g., energy, slow speed) nodes per grid are alive • Resolution between N nodes

17. GAF interactions with ad hoc routing • Duty cycle is based on application- and system-level information • GAF decision to turn radio on/off is independent of routing protocols • Packet loss • GAF can inform routing protocol of impending suspension • Interaction between clustering (topology control) and routing is important • If N nodes per grid are alive, seamless transfer is possible? • Kind of grid-wise anycasting • MAC header: dest field is broadcast address • NWK header: src, dest, next-hop grid-id

18. Simulation - Network Lifetime

19. Simulation –Data Delivery